Meruva L.
Junior AI/ML Engineer
Open to offersNew to PlatformAbout
Meruva L., known for her work as an AI/ML Engineer, resides in Bengaluru, India, bringing hands-on expertise in developing machine learning models and deep learning pipelines, especially for recommendation systems and medical image classification within real-world applications. She excels in crafting maintainable Python scripts and specializes in frameworks like TensorFlow, PyTorch, and Scikit-learn. Her experience spans across data preprocessing and feature engineering, leveraging NLP techniques, including TF-IDF and cosine similarity, to optimize semantic matching accuracy. In her role at Arka Mediaworks, Meruva demonstrated her proficiency by implementing a recommendation system and a deep learning image classification pipeline, ensuring robust model performance backed by accuracy, precision, and recall metrics. Aware of responsible AI principles, she is committed to ethical, production-ready AI solutions, involving comprehensive data analysis and communication for both technical and non-technical stakeholders.
Experience
AI/ML Engineer Intern
Arka Mediaworks · 2025 — 2026Designed a content-based machine learning recommendation system utilizing TF-IDF vectorization and cosine similarity, building and testing an end-to-end ML pipeline from raw data to model output. Conducted data preprocessing, feature engineering, and exploratory data analysis on structured datasets using Python (Pandas, NumPy) to enhance data quality and optimize inputs for ML workflows. Assessed model performance through standard metrics such as accuracy, precision, recall, and F1-score, while iterating on the pipeline to enhance recommendation relevance. Developed modular, reusable Python code for larger AI-driven applications, incorporating clean coding practices and version control through Git and GitHub. Produced clear reports of analytical findings and model insights aimed at both technical and non-technical stakeholders, reflecting an awareness of responsible AI communication.Medical Image Classification System
ProjectCreated a deep learning image classification pipeline using CNN architecture (TensorFlow/PyTorch) for categorizing medical images into clinically relevant groups. Applied various preprocessing techniques, such as resizing and data augmentation, to improve model robustness and generalization. Evaluated and optimized model performance with metrics like accuracy, precision, recall, and F1-score, incorporating hyperparameter tuning to enhance prediction quality.Content-Based Movie Recommendation System
ProjectDeveloped a machine learning recommendation engine that employed NLP techniques (TF-IDF vectorization, cosine similarity) on movie metadata to create top-N personalized recommendations. Executed text preprocessing and feature engineering to enhance semantic matching accuracy while building the solution with modular Python code suitable for integration into larger AI-driven application pipelines.
Skills & Expertise
Education
- B.Tech in Computer Science and EngineeringJNTUA College of Engineering, Pulivendula · 2021 — 2025
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